Update app.py

app.py

@@ -14,12 +14,7 @@ from src.flux.sampling import denoise_controlnet, get_noise, get_schedule, prepa
 from src.flux.util import load_ae, load_clip, load_t5, load_flow_model, load_controlnet, load_safetensors
 
 # Download and load the ControlNet model
-model_url = "https://huggingface.co/XLabs-AI/flux-controlnet-canny-v3/resolve/main/flux-canny-controlnet-v3.safetensors?download=true"
-model_path = "./flux-canny-controlnet-v3.safetensors"
-if not os.path.exists(model_path):
-    response = requests.get(model_url)
-    with open(model_path, 'wb') as f:
-        f.write(response.content)
+controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Union'
 
 # Source: https://github.com/XLabs-AI/x-flux.git
 name = "flux-dev"
@@ -35,10 +30,7 @@ def load_models():
     clip = load_clip(device)
     model = load_flow_model(name, device=device)
     ae = load_ae(name, device=device)
-    controlnet = load_controlnet(name, device).to(device).to(torch.bfloat16)
-
-    checkpoint = load_safetensors(model_path)
-    controlnet.load_state_dict(checkpoint, strict=False)
+    controlnet = load_controlnet(controlnet_model, device).to(device).to(torch.bfloat16)
 
 load_models()
 
@@ -98,8 +90,7 @@ def generate_image(prompt, control_image, control_mode, num_steps=50, guidance=4
         x = get_noise(1, height, width, device=torch_device, dtype=torch.bfloat16, seed=seed)
         inp_cond = prepare(t5=t5, clip=clip, img=x, prompt=prompt)
 
-        controlnet.control_mode = control_modes.index(control_mode)  # Set the control mode directly in the controlnet model
-        x = denoise_controlnet(model, **inp_cond, controlnet=controlnet, timesteps=timesteps, guidance=guidance, controlnet_cond=controlnet_cond)
+        x = denoise_controlnet(model, **inp_cond, controlnet=controlnet, timesteps=timesteps, guidance=guidance, controlnet_cond=controlnet_cond, control_mode=control_modes.index(control_mode))
         
         x = unpack(x.float(), height, width)
         x = ae.decode(x)